code: def __init__(
      self,
      encoder_type: str,
      encoder_input_dims: int,
      encoder_multi_res: int,
      num_output_dims: int,
      net_cfg: Dict,
  ):
      super().__init__()
  
      self.encoder, self.encoder_output_dims = get_encoder(
          encoder_type,
          input_dim=encoder_input_dims,
          multires=encoder_multi_res,
      )
      self.background_net = MLP(
          num_input_dims=self.encoder_output_dims,
          num_output_dims=num_output_dims,
          num_hidden_dims=net_cfg.num_hidden_dims,
          num_layers=net_cfg.num_layers,
          bias=net_cfg.bias,
      )
  
file_path: NeMo/nemo/collections/multimodal/modules/nerf/background/torchngp_background.py
imports: from typing import Dict
  import torch
  from nemo.collections.multimodal.modules.nerf.background.nerf_background_base import NeRFBackgroundBase
  from nemo.collections.multimodal.modules.nerf.geometry.layers import MLP
  from nemo.collections.multimodal.modules.nerf.utils.torch_ngp.encoding import get_encoder
label_desc: Use image node_id 1 to create a new TorchNGPBackground object from inherited base classes: NeRFBackgroundBase with example: obj = TorchNGPBackground(encoder_type, encoder_input_dims, encoder_multi_res, num_output_dims, net_cfg)